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http://dx.doi.org/10.6109/jkiice.2017.21.4.698

Predictive Control for Mobile Robots Using Genetic Algorithms  

Son, Hyun-sik (Department of Electrical and Computer Engineering, Pusan National University)
Park, Jin-hyun (Dep. of Mechatronics Engineering, Kyeongnam National University of Science and Technology)
Choi, Young-kiu (Department of Electrical Engineering, Pusan National University)
Publication Information
Journal of the Korea Institute of Information and Communication Engineering / v.21, no.4, 2017 , pp. 698-707 More about this Journal
Abstract
This paper deals with predictive control methods of mobile robots for reference trajectory tracking control. Predictive control methods using predictive model are known as effective schemes that minimize the future errors between the reference trajectories and system states; however, the amount of real-time computation for the predictive control are huge so that their applications were limited to slow dynamic systems such as chemical processing plants. Lately with high computing power due to advanced computer technologies, the predictive control methods have been applied to fast systems such as mobile robots. These predictive controllers have some control parameters related to control performance. But these parameters have not been optimized. In this paper we employed the genetic algorithm to optimize the control parameters of the predictive controller for mobile robots. The improved performances of the proposed control method are demonstrated by the computer simulation studies.
Keywords
mobile robots; predictive control; genetic algorithm; control parameters;
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Times Cited By KSCI : 1  (Citation Analysis)
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